• Media type: E-Article
  • Title: The influence of ergodicity on risk affinity of timed and non-timed respondents
  • Contributor: Vanhoyweghen, Arne; Verbeken, Brecht; Macharis, Cathy; Ginis, Vincent
  • Published: Springer Science and Business Media LLC, 2022
  • Published in: Scientific Reports, 12 (2022) 1
  • Language: English
  • DOI: 10.1038/s41598-022-07613-6
  • ISSN: 2045-2322
  • Keywords: Multidisciplinary
  • Origination:
  • Footnote:
  • Description: AbstractExpected values are the metric most often used to judge human decision-making; when humans make decisions that do not optimize expected values, these decisions are considered irrational. However, while convenient, expected values do not necessarily describe the evolution of an individual after making a series of decisions. This dichotomy lies at the core of ergodicity breaking, where the expected value (ensemble average) differs from the temporal average of one individual. In this paper, we explore whether the intuition behind human decision-making optimizes for expected values or instead takes time growth rates into account. We do this using several stated choice experiments, where participants choose between two stochastic bets and try to optimize their capital. To evaluate the intuitive choice, we compare two groups, with and without perceived time pressure. We find a significant difference between the responses of the timed and the control group, depending on the dynamic of the choices. In an additive dynamic, where ergodicity is not broken, we observe no effect of time pressure on the decisions. In the non-ergodic, multiplicative setting, we find a significant difference between the two groups. The group that chooses under time pressure is more likely to make the choice that optimizes the experiment’s growth rate. The results of this experiment contradict the idea that people are irrational decision-makers when they do not optimize their expected value. The intuitive decisions deviate more from the expected value optimum in the non-ergodic part of our experiment and lead to more optimal decisions.
  • Access State: Open Access